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Plant Diseases Dataset
- universe.roboflow.com
zipUpdated Nov 15, 2022
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EmailClick to copy linkLink copiedCiteCSUEB (2022). Plant Diseases Dataset [Dataset]. https://universe.roboflow.com/csueb/plant-diseases-c2yf6zipAvailable download formatsDataset updatedNov 15, 2022Dataset authored and provided byCSUEBLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyVariables measuredDiseases Bounding BoxesDescriptionHere are a few use cases for this project:
Agricultural Health Monitoring: The "Plant-diseases" model can be used by farmers to monitor the health status of their crops in real time. Identifying diseases early can help apply preventative measures promptly, significantly improving crop yield.
Digital Farming Apps: This model can be incorporated into agricultural mobile applications to help farmers identify plant diseases by simply taking a picture of their crops. The app can provide instant diagnosis and treatment recommendations.
Research and Development: The "Plant-diseases" model can provide valuable data for agricultural researchers studying crop diseases. By using the model, researchers can quickly categorize different types of plant diseases and identify patterns and correlations.
Smart Farming Equipment: This model can be integrated into smart farming equipment such as drones or robotics for crop surveillance. Such equipment can scan large areas of field quickly, identifying unhealthy plants and alerting farmers about potential disease outbreaks.
Educational Tool: Institutions teaching agriculture or botany-related subjects can use this model as a practical tool for educating students about plant diseases. They can easily show what different types of diseases look like and explain how they affect plants.
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Plant_disease Dataset
- universe.roboflow.com
zipUpdated Nov 18, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteAkash (2022). Plant_disease Dataset [Dataset]. https://universe.roboflow.com/akash-jxfmg/plant_disease-imdag/model/1zipAvailable download formatsDataset updatedNov 18, 2022Dataset authored and provided byAkashLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyVariables measuredDiseases Bounding BoxesDescriptionHere are a few use cases for this project:
Agricultural Health Monitoring: This model could be used widely in farming to monitor the health of crops in real-time. Farmers could capture images of the plants, and the model would alert them if a disease is detected, thereby enabling early diagnosis and treatment to prevent widespread damage and loss.
Greenhouse Maintenance: Commercial greenhouses could use the model to regularly check their plants for signs of disease. This would ensure optimal plant health and crop yield by detecting diseases before they can spread throughout the greenhouse.
Botanical Research: Researchers investigating plant diseases could utilize this model to identify the presence and progression of these specific plant diseases. It can streamline the research process by reducing manual examination needs.
Home Gardening Application: An application could be developed for home gardeners to input pictures of their plants and receive information on the health of their plants. If a disease is detected, the app can provide the recommended course of treatment.
Automated Farming Equipment: This model could be integrated into automated farming machinery, such as drones or other remote imaging devices. This would allow for extensive fields or difficult to access areas to be surveyed for disease symptoms without manual labor.
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FacebookTwitterEmailAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Here are a few use cases for this project:
Agricultural Health Monitoring: The "Plant-diseases" model can be used by farmers to monitor the health status of their crops in real time. Identifying diseases early can help apply preventative measures promptly, significantly improving crop yield.
Digital Farming Apps: This model can be incorporated into agricultural mobile applications to help farmers identify plant diseases by simply taking a picture of their crops. The app can provide instant diagnosis and treatment recommendations.
Research and Development: The "Plant-diseases" model can provide valuable data for agricultural researchers studying crop diseases. By using the model, researchers can quickly categorize different types of plant diseases and identify patterns and correlations.
Smart Farming Equipment: This model can be integrated into smart farming equipment such as drones or robotics for crop surveillance. Such equipment can scan large areas of field quickly, identifying unhealthy plants and alerting farmers about potential disease outbreaks.
Educational Tool: Institutions teaching agriculture or botany-related subjects can use this model as a practical tool for educating students about plant diseases. They can easily show what different types of diseases look like and explain how they affect plants.